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The efiects of the flbroglandular tissue distribution of the breast on data-independent microwave imaging algorithms are investigated in this paper. A data-independent beamformer is a beamformer whose weights do not depend on the array data and are chosen, based on a channel model, to compensate for path-dependent attenuation and phase efiects. The efiectiveness and robustness of data-independent UWB beamforming algorithms relies upon two speciflc characteristics of breast tissue at microwave frequencies: Firstly, that there exists a signiflcant dielectric contrast between cancerous tissue and normal healthy breast tissue; secondly, that the propagation, attenuation and phase characteristics of normal tissue allow for constructive addition of the UWB returns using the Confocal Microwave Imaging (CMI) technique. However, two recent studies by Lazebnik et al. have highlighted a signiflcant dielectric contrast between normal adipose and flbroglandular tissue within the breast. These results suggest a much more di-cult imaging scenario where clutter due to flbroglandular tissue is a signiflcant concern and that constructive addition of backscattered signals is potentially much more problematic than previously assumed. In this paper, three existing data-independent beamformers are tested on several difierent breast models, examining the efiect of difierent flbroglandular tissue distribution on the performance of the data-independent imaging algorithms.

EFFECTS OF FIBROGLANDULAR TISSUE DISTRIBUTION ON DATA-INDEPENDENT BEAMFORMING ALGORITHMS